🎯 This shiny app is aiming to explore the COVID-19 data of two neighboring countries: Chile and Bolivia. It’s interesting to explore the differences of how COVID-19 spread in countries near each other.
📁 This app contains the daily data of:
Newly confirmed, recovered and dead cases
The cumulative cases of confirmed, recovered and dead cases
The ratio of recovery and death
👩💻 Main sessions of this app:
Daily cases data of your selected country.
You can select the name of the country to see it’s daily data of COVID-19.
Compare the trends of new confirmed cases of Chile and Bolivia by your input date range.
You can select the start and end of date, to compare the trends of newly confirmed cases in the two countries in your selected time period.
Compare the trends of your selected indicator of Chile and Bolivia.
You can select an indicator from: confirm_cum, recover_cum, death_cum, recover_ratio, death_ratio, and compare the trends of your selected indicator between the two countries to see trends in the spread of the epidemic in these two countries.
Automatically updated data: This shiny app uses the data from the Github version of “coronavirus” package, which is updated on a daily bases. The update_dataset() function of this package enable our shiny app updates it’s data automatically as long as there’s new data in the original data source – Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) Coronavirus repository.
Customizable analysis time period: This shiny app contains a customizable date range input to enable users select the date range they are interested in to see the trend of newly confirmed cases in that time period. For example, if you would like to see the effect of a COVID related policy, you can select the time period around the date which the policy was issued, to see whether it works as expected.
Multiple indicators: In this app, for each country, on each day, it provides the data of newly confirmed / recovered / dead cases (confirmed / recovered / death), cumulative confirmed / recovered / dead cases (confirm_cum / recover_cum / death_cum), percentage of recovered / dead cases (recover_ratio / death_ratio).
Comparison between countries: At this stage, this app was designed to compare the daily data and indicators between Chile and Bolivia. Since the two countries are near each other, it’s reasonable to compare their data trends and figure out why the numbers are different.
The use of “observeEvent” and “reactive” functions: I think it’s better to make all the plots share the user’s input, and this will help the app become more powerful to explore the COVID-19 data. However, I haven’t managed to make these functions work properly.
Visual appealing: When I went through the official COVID-19 dashboards, I found that the typesetting was very compact, which was also lacking in my work.
Technical limitation: There are only two countries to select currently. Unable to select any country to explore it’s data, since I haven’t managed to pull all the country names as a list.
User experience: Using Github (dev) version R packages may affect the user experience of those who are not familiar with the devtools package. In addition, the update of the data set will take a few seconds, which slows down the app when it was run for the first time.
Copyright © 2020 Yan Ma, Coronavirus Track Website.


About
Simon’s Blog
Blog
Tackling AS2 with JBoss Fuse
Secure Financial Messaging with JBoss Fuse & A-MQ
JBoss A-MQ 6.2 Performance Tuning Adventures
Creating a two-way SSL SOAP client using Apache Camel CXF
Managed File Transfer (MFT) the RESTFul way


I have done B.Tech in Computer Science from Glocal University, Saharanpur. I’m eager to learn and I love solving technical problems . My major areas of interest are data structures, algorithms, mathematics, solving real world data science problems.
I have good experience with Machine Learning, Deep Learning and NLP. I have worked on scikit-learn, XGBoost and keras for solving various real world classification, regression and clustering problems using Naive Bayes,Logistic Regression, SVM, SVD, MLP and other techniques. I have posted my Data Science projects here.
I did my Summer 2015 Training at Hewlett-Packard Education Services(HPES), Noida in Java where I secured 'A' grade.
I did my Final Year Project on Comparison of different machine Learning Algorithms on a dataset and compared their accuracy for each model built. I've also set up multi-cluster environment for data processing in my University using Apache Hadoop. I've some knowledge on Apache Hadoop, Pig.
Build a recommendation system for apparel which gives the most similar products using amazon dataset. Techniques used Tfidf-W2Vec, VGG-16.
View More..
Predict the movies for users with the help of surprise library and SVD. Trained different models and used the result of each model as feature to the next model with the final model as XgBoost to reduce RMSE.
View More..
Exploratory Data Analysis of Cancer data from kaggle and running various models and plotting confusion matrix and return probability score to make model interpretable. Techniques used Tfidf, Naive Bayes, Logistic Regression, SVM, Random Forest.
View More..
Predicting whether a question is duplicate or not and predict if the question is duplicate from quora dataset and reducing the loss using hyperparameter tuning. Techniques used : Avg-W2Vec, Logistic Regression, Linear SVM and XGBoost.
View More..
Predict the pick up density of cabs at a given particular time and a location in New York City using simple models such as Rolling Window and its variants and Regression Models such as Random Forest and XGBoost and using Time Series Forecasting and Fourier Features.
View More..
Visualize the data set and apply various models and see which one performs better with respect to other on various performance metrics. Techniques used : KNN, Naive-Bayes, Logistic Regression, Decision Tree.
View More..
Found out the top tfidf vectors and then find the co-occurrence matrix and we use Truncated SVD to find word-vectors and find the top words that are clustered together using KMeans and plot them using WordCloud according to top tfidf. Techniques used: TF-IDF, Truncated SVD, Kmeans++.
View More..
Predicted the tag related to the question and improved the micro-averaged-f1-score with hyperparameter tuning of Logistic Regression and SVM.
View More..


This tool uses the ASE and pymatgen libraries for structure manipulation, and spglib for symmetry detection. The tool is based upon the tools-barebone framework developed by the Materials Cloud team.
We acknowledge funding from the MARVEL National Centre of Competence in Research of the Swiss National Science Foundation (SNSF) (grant agreement ID 51NF40-182892), the European Centre of Excellence MaX ``Materials design at the Exascale'' (grant no. 824143), the swissuniversities P-5 ``Materials Cloud'' project (grant agreement ID 182-008), the Graphene Flagship, the RC Grant Hetero2D, the EPSRC Grants EP/509K01711X/1, EP/K017144/1, EP/N010345/1, EP/M507799/5101 and EP/L016087/1, the Italian Ministry for University and Research through the Levi--Montalcini program, and from SNSF through the Ambizione program (grant 174056). We thank L. Talirz for support during the deployment of this tool on Materials Cloud.


Package org.drip.graph.softheap
Class KaplanZwickTree<KEY extends java.lang.Comparable<KEY>,ITEM>
java.lang.Object
org.drip.graph.softheap.KaplanZwickTree<KEY,ITEM>
public class KaplanZwickTree<KEY extends java.lang.Comparable<KEY>,ITEM>
extends java.lang.Object
KaplanZwickTree implements the Tree described in Kaplan and Zwick (2009). The References are:
- Chazelle, B. (2000): The Discrepancy Method: Randomness and Complexity https://www.cs.princeton.edu/~chazelle/pubs/book.pdf
- Chazelle, B. (2000): The Soft Heap: An Approximate Priority Queue with Optimal Error Rate Journal of the Association for Computing Machinery 47 (6) 1012-1027
- Chazelle, B. (2000): A Minimum Spanning Tree Algorithm with Inverse-Ackerman Type Complexity Journal of the Association for Computing Machinery 47 (6) 1028-1047
- Kaplan, H., and U. Zwick (2009): A simpler implementation and analysis of Chazelle's Soft Heaps https://epubs.siam.org/doi/abs/10.1137/1.9781611973068.53?mobileUi=0
- Pettie, S., and V. Ramachandran (2008): Randomized Minimum Spanning Tree Algorithms using Exponentially Fewer Random Bits ACM Transactions on Algorithms 4 (1) 1-27
- Module = Computational Core Module
- Library = Graph Algorithm Library
- Project = Graph Optimization and Tree Construction Algorithms
- Package = Soft Heap - Approximate Priority Queue
- Author:
- Lakshmi Krishnamurthy
-
Constructor Summary
Constructors Constructor Description KaplanZwickTree(KaplanZwickBinaryNode<KEY,ITEM> root)
KaplanZwickTree Constructor -
Method Summary
Modifier and Type Method Description static <KEY extends java.lang.Comparable<KEY>, ITEM>
KaplanZwickTree<KEY,ITEM>EquiRankTreeMerge(KaplanZwickTree<KEY,ITEM> tree1, KaplanZwickTree<KEY,ITEM> tree2)
Merge Two Trees with Identical Ranksstatic <KEY extends java.lang.Comparable<KEY>, ITEM>
KaplanZwickTree<KEY,ITEM>Initial(boolean minHeap, int r, PriorityQueueEntry<KEY,ITEM> entry)
Construct an Initial Tree with a single EntryKaplanZwickTree<KEY,ITEM>
next()
Retrieve the Next Tree in the ListKaplanZwickTree<KEY,ITEM>
prev()
Retrieve the Previous Tree in the Listint
rank()
Retrieve the Rank of the TreeKaplanZwickBinaryNode<KEY,ITEM>
root()
Retrieve the Root of the TreeKaplanZwickTree<KEY,ITEM>
rootTree()
Generate a Stand-alone Tree with the Root Node alone in its Listboolean
setNext(KaplanZwickTree<KEY,ITEM> next)
(Re-)set the Next Treeboolean
setPrev(KaplanZwickTree<KEY,ITEM> prev)
(Re-)set the Previous Treeboolean
setRoot(KaplanZwickBinaryNode<KEY,ITEM> root)
(Re-)set the Rootboolean
setSuffixExtremum(KaplanZwickTree<KEY,ITEM> suffixExtremum)
(Re-)set the Suffix Extremum TreeKaplanZwickTree<KEY,ITEM>
suffixExtremum()
Retrieve the Extremum ckey Tree among those following this in the Liststatic <KEY extends java.lang.Comparable<KEY>, ITEM>
booleanUpdateSuffixExtremum(KaplanZwickTree<KEY,ITEM> tree)
Update the Suffix Extremum of all Trees at and preceding the specified TreeMethods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
-
Constructor Details
-
KaplanZwickTree
KaplanZwickTree Constructor- Parameters:
root
- Root of the Current Tree- Throws:
java.lang.Exception
- Thrown if the Inputs are Invalid
-
-
Method Details
-
UpdateSuffixExtremum
public static <KEY extends java.lang.Comparable<KEY>, ITEM> boolean UpdateSuffixExtremum(KaplanZwickTree<KEY,ITEM> tree)Update the Suffix Extremum of all Trees at and preceding the specified Tree- Type Parameters:
KEY
- Key TypeITEM
- Item Type- Parameters:
tree
- Specified Tree- Returns:
- TRUE - Update Suffix Extremum successfully completed
-
EquiRankTreeMerge
public static <KEY extends java.lang.Comparable<KEY>, ITEM> KaplanZwickTree<KEY,ITEM> EquiRankTreeMerge(KaplanZwickTree<KEY,ITEM> tree1, KaplanZwickTree<KEY,ITEM> tree2)Merge Two Trees with Identical Ranks- Type Parameters:
KEY
- Key TypeITEM
- Item Type- Parameters:
tree1
- Tree #1tree2
- Tree #2- Returns:
- The Merged Tree
-
Initial
public static <KEY extends java.lang.Comparable<KEY>, ITEM> KaplanZwickTree<KEY,ITEM> Initial(boolean minHeap, int r, PriorityQueueEntry<KEY,ITEM> entry)Construct an Initial Tree with a single Entry- Type Parameters:
KEY
- Key TypeITEM
- Item Type- Parameters:
minHeap
- Min Heap Flagr
- The R Parameterentry
- The Entry- Returns:
- The Initial Tree with a single Entry
-
root
Retrieve the Root of the Tree- Returns:
- The Root
-
prev
Retrieve the Previous Tree in the List- Returns:
- The Previous Tree in the List
-
next
Retrieve the Next Tree in the List- Returns:
- The Next Tree in the List
-
suffixExtremum
Retrieve the Extremum ckey Tree among those following this in the List- Returns:
- The Extremum ckey Tree among those following this in the List
-
rank
public int rank()Retrieve the Rank of the Tree- Returns:
- Rank of the Tree
-
setRoot
(Re-)set the Root- Parameters:
root
- The Root- Returns:
- TRUE - The Root successfully (re-)set
-
setPrev
(Re-)set the Previous Tree- Parameters:
prev
- The Previous Tree- Returns:
- TRUE - The Previous Tree successfully (re-)set
-
setNext
(Re-)set the Next Tree- Parameters:
next
- The Next Tree- Returns:
- TRUE - The Next Tree successfully (re-)set
-
setSuffixExtremum
(Re-)set the Suffix Extremum Tree- Parameters:
suffixExtremum
- The Suffix Extremum- Returns:
- TRUE - The Suffix Extremum Tree successfully (re-)set
-
rootTree
Generate a Stand-alone Tree with the Root Node alone in its List- Returns:
- Stand-alone Tree with the Root Node alone in its List
-


| Size | {{tx.size}} (bytes) | |
| Fee Rate | {{$root.currency.getConvertion((tx.fees * 1000) / tx.size) + ' per kB' || ((tx.fees * 1000) / tx.size) + 'AXE per kB'}} | |
| Received Time | {{tx.time * 1000|date:'medium'}} | N/A |
| Mined Time | {{tx.blocktime * 1000|date:'medium'}} | N/A |
| Included in Block | Unconfirmed | |
| LockTime | {{tx.locktime}} | |
| Coinbase |
{{tx.vin[0].coinbase}}
|


Welcome to BurgerHeaven
Select burger
This is where you execute burger selection
{{name}}
{{burger.name}}
- {{burger.kCal}} kCal
- Contains lactose
- Contains gluten
Customer information
Delivery information:
{{orderId}}


--- layout: archive title: Zulip Chat Archive permalink: /stream/116395-maths/topic/is_open.20.7Btrue.7D.html ---
how to prove is_open {true}
? This should be very easy.
The topology on Prop
is generate_from {true}
library_search
says exact is_open_discrete {to_bool true}
Sorry, my message is for true
in bool
. In Prop
, library_search
says exact is_open_singleton_true
.
simp
also works, by the way.
MWE:
import topology.order example : is_open ({true} : set Prop) := is_open_singleton_true
but that lemma is just a thin wrapper around
example : is_open ({true} : set Prop) := generate_open.basic _ (by exact or.inl rfl)
Last updated: Apr 24 2020 at 19:02 UTC


Table Of Contents
kivy.core.audio のソースコード
'''
Audio
=====
Load an audio sound and play it with::
from kivy.core.audio import SoundLoader
sound = SoundLoader.load('mytest.wav')
if sound:
print("Sound found at %s" % sound.source)
print("Sound is %.3f seconds" % sound.length)
sound.play()
You should not use the Sound class directly. The class returned by
:func:`SoundLoader.load` will be the best sound provider for that particular
file type, so it might return different Sound classes depending the file type.
Event dispatching and state changes
-----------------------------------
Audio is often processed in parallel to your code. This means you often need to
enter the Kivy :func:`eventloop <kivy.base.EventLoopBase>` in order to allow
events and state changes to be dispatched correctly.
You seldom need to worry about this as Kivy apps typically always
require this event loop for the GUI to remain responsive, but it is good to
keep this in mind when debugging or running in a
`REPL <https://en.wikipedia.org/wiki/Read%E2%80%93eval%E2%80%93print_loop>`_
(Read-eval-print loop).
.. versionchanged:: 1.10.0
The pygst and gi providers have been removed.
.. versionchanged:: 1.8.0
There are now 2 distinct Gstreamer implementations: one using Gi/Gst
working for both Python 2+3 with Gstreamer 1.0, and one using PyGST
working only for Python 2 + Gstreamer 0.10.
.. note::
The core audio library does not support recording audio. If you require
this functionality, please refer to the
`audiostream <https://github.com/kivy/audiostream>`_ extension.
'''
__all__ = ('Sound', 'SoundLoader')
from kivy.logger import Logger
from kivy.event import EventDispatcher
from kivy.core import core_register_libs
from kivy.compat import PY2
from kivy.resources import resource_find
from kivy.properties import StringProperty, NumericProperty, OptionProperty, \
AliasProperty, BooleanProperty, BoundedNumericProperty
from kivy.utils import platform
from kivy.setupconfig import USE_SDL2
from sys import float_info
[ドキュメント]class SoundLoader:
'''Load a sound, using the best loader for the given file type.
'''
_classes = []
@staticmethod
[ドキュメント] def register(classobj):
'''Register a new class to load the sound.'''
Logger.debug('Audio: register %s' % classobj.__name__)
SoundLoader._classes.append(classobj)
@staticmethod
[ドキュメント] def load(filename):
'''Load a sound, and return a Sound() instance.'''
rfn = resource_find(filename)
if rfn is not None:
filename = rfn
ext = filename.split('.')[-1].lower()
if '?' in ext:
ext = ext.split('?')[0]
for classobj in SoundLoader._classes:
if ext in classobj.extensions():
return classobj(source=filename)
Logger.warning('Audio: Unable to find a loader for <%s>' %
filename)
return None
[ドキュメント]class Sound(EventDispatcher):
'''Represents a sound to play. This class is abstract, and cannot be used
directly.
Use SoundLoader to load a sound.
:Events:
`on_play`: None
Fired when the sound is played.
`on_stop`: None
Fired when the sound is stopped.
'''
source = StringProperty(None)
'''Filename / source of your audio file.
.. versionadded:: 1.3.0
:attr:`source` is a :class:`~kivy.properties.StringProperty` that defaults
to None and is read-only. Use the :meth:`SoundLoader.load` for loading
audio.
'''
volume = NumericProperty(1.)
'''Volume, in the range 0-1. 1 means full volume, 0 means mute.
.. versionadded:: 1.3.0
:attr:`volume` is a :class:`~kivy.properties.NumericProperty` and defaults
to 1.
'''
pitch = BoundedNumericProperty(1., min=float_info.epsilon)
'''Pitch of a sound. 2 is an octave higher, .5 one below. This is only
implemented for SDL2 audio provider yet.
.. versionadded:: 1.10.0
:attr:`pitch` is a :class:`~kivy.properties.NumericProperty` and defaults
to 1.
'''
state = OptionProperty('stop', options=('stop', 'play'))
'''State of the sound, one of 'stop' or 'play'.
.. versionadded:: 1.3.0
:attr:`state` is a read-only :class:`~kivy.properties.OptionProperty`.'''
loop = BooleanProperty(False)
'''Set to True if the sound should automatically loop when it finishes.
.. versionadded:: 1.8.0
:attr:`loop` is a :class:`~kivy.properties.BooleanProperty` and defaults to
False.'''
#
# deprecated
#
def _get_status(self):
return self.state
status = AliasProperty(_get_status, None, bind=('state', ))
'''
.. deprecated:: 1.3.0
Use :attr:`state` instead.
'''
def _get_filename(self):
return self.source
filename = AliasProperty(_get_filename, None, bind=('source', ))
'''
.. deprecated:: 1.3.0
Use :attr:`source` instead.
'''
__events__ = ('on_play', 'on_stop')
def on_source(self, instance, filename):
self.unload()
if filename is None:
return
self.load()
[ドキュメント] def get_pos(self):
'''
Returns the current position of the audio file.
Returns 0 if not playing.
.. versionadded:: 1.4.1
'''
return 0
def _get_length(self):
return 0
length = property(lambda self: self._get_length(),
doc='Get length of the sound (in seconds).')
[ドキュメント] def load(self):
'''Load the file into memory.'''
pass
[ドキュメント] def unload(self):
'''Unload the file from memory.'''
pass
[ドキュメント] def play(self):
'''Play the file.'''
self.state = 'play'
self.dispatch('on_play')
[ドキュメント] def stop(self):
'''Stop playback.'''
self.state = 'stop'
self.dispatch('on_stop')
[ドキュメント] def seek(self, position):
'''Go to the <position> (in seconds).
.. note::
Most sound providers cannot seek when the audio is stopped.
Play then seek.
'''
pass
def on_play(self):
pass
def on_stop(self):
pass
# Little trick here, don't activate gstreamer on window
# seem to have lot of crackle or something...
audio_libs = []
if platform in ('macosx', 'ios'):
audio_libs += [('avplayer', 'audio_avplayer')]
try:
from kivy.lib.gstplayer import GstPlayer # NOQA
audio_libs += [('gstplayer', 'audio_gstplayer')]
except ImportError:
pass
audio_libs += [('ffpyplayer', 'audio_ffpyplayer')]
if USE_SDL2:
audio_libs += [('sdl2', 'audio_sdl2')]
else:
audio_libs += [('pygame', 'audio_pygame')]
libs_loaded = core_register_libs('audio', audio_libs)


Architect
Edit Javascript templates in various engines
offline enabled
Engine:
Reset
Template
View
Result
Fork me on GitHub


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Hero let's you...
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Cras mattis consectetur purus sit fermentum
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Cras mattis consectetur purus sit fermentum
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World’s most advanced App
with High-Tech solutions
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The Strong museum has collected
more than 55,000 video games and related artifacts
from the history of gaming.
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The Strong museum has collected
more than 55,000 video games and related artifacts
from the history of gaming.
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Features All Joined Together
in One App
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Sync
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Computer manufacturer
Lenovo is getting flak...
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Share
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Hero is a mobile payment system that could...
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Stats
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Computer manufacturer
Lenovo is getting flak...
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Responsive layout
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Tanjin is one of nearly
2,000 people to have landed on Italy’s southernmost.
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Retina Ready
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Tanjin is one of nearly
2,000 people to have landed on Italy’s southernmost.
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Various Skins
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Tanjin is one of nearly
2,000 people to have landed on Italy’s southernmost.
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Great Performance
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Tanjin is one of nearly
2,000 people to have landed on Italy’s southernmost.
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Userfriendly menus
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Tanjin is one of nearly
2,000 people to have landed on Italy’s southernmost.
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Social share
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Tanjin is one of nearly
2,000 people to have landed on Italy’s southernmost.
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Interested in our App?
Muriel Bowser’s administration says move is unrelated to
charges that encryption caused failures in Metro.
Request a quote
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Now, only after a thorough review of your audience and its needs, is the time to think about you. What do you have to offer in relation to your audience’s needs? How can you be a real part of the solution? Perhaps you can add some muscle to their weakest parts and make them look like heroes. This is your value proposition.
An innovative American company was acquired by a large conservative European firm with a more formal corporate culture and less diverse workforce. The executives of the San Francisco company were concerned that with recent leadership changes, management looked less diverse, especially in the area of engineering. Celia, a process engineer, was able to differentiate herself by adding diversity leader to her positioning and leveraging her role as president of a national organization of female engineers. She became an asset to the executive team as they looked to raise the visibility of the company as an inclusive employer.
When applying for a job, every applicant will say he or she is a skilled programmer, accountant, manager—or whatever the title may be. That is a given. But what is your cake that adds differentiating value?
If you are interviewing with a company that is light on experience, and you’ve got a lot, emphasize your lengthy track record. If the opposite is true, emphasize your fresh perspective.
How can you help them reduce burdensome costs? Boost lagging sales? Change their culture? Find a pain point that your particular audience has today, and show how you can be—or at least be an important part of—the cure.
After watching the video above, enter a value for the Value Proposition field:


Introduction
-
Nginx : light-weight Web server
-
generally used as HTTP Web Server, Reverse Proxy Server, Load Balancer
-
Reverse Proxy
-
Proxy server : is a server that acts as an intermediary between a client and the server
-
Load balancing : Proxies distribute requests to a group of servers,
-
Encryption : Proxies encrypt the data to keep it from being read during transfer.
-
Caching : Proxies speed up access to information by storing the results of user requests in the server’s cache for a specified time
-
-
-
Load Balancer
-
-
-
General Usage
-
Nginx as a independent docker container
-
Nginx as a process in web framework container
-
1. Start Nginx as a independent docker container
-
Run Nginx in a independent docker container
-
docker pull nginx
-
docker run --name nginx-server -d -p 80:80 nginx
-
-
Customize nginx container :
docker build -t nginx:test .
# /nginx/nginx.conf # default.conf file includes *.conf by "include /etc/nginx/conf.d/*.conf;" upstream app { server flask:5000; # UPSTREAM_CONTAINER_NAME:PORT } server { listen 80; # NGINX_PORT location / { proxy_pass http://app; # we defined upstream app above } }
# Dockerfile.nginx FROM nginx:latest COPY default.conf /etc/nginx/conf.d/default.conf CMD ["nginx", "-g", "daemon off;"]
-
Run docker-compose :
docker-compose up
version: '3' services: flask: container_name: flask image: "flask:test" ports: - "5000:5000" networks: - backend nginx: container_name: nginx image: "nginx:test" ports: - "80:80" networks: - backend networks: # basic bridge network backend: driver: bridge
2. Start Nginx as a process in web app (WSGI) container
-
Prepare nginx.conf
```nginx # /nginx/nginx.conf # default.conf file includes *.conf by "include /etc/nginx/conf.d/*.conf;" upstream app { server localhost:{MAIN_PORT}; # upstream is running in same container } server { listen ${NGINX_PORT}; # NGINX_PORT will be filled later location / { proxy_pass http://app; # we defined upstream "app" above } }
-
Install Nginx in Dockerfile
# Dockerfile.web ARG PYTHON_VERSION FROM python:${PYTHON_VERSION}-slim USER root RUN apt-get -y update \ && apt-get -y install nginx \ && apt-get install gettext-base RUN pip install redis\ gunicorn\ uvicorn\ fastapi RUN mkdir -p /opt COPY bin /opt/bin COPY src /opt/src COPY nginx.conf /opt/nginx.conf
-
Run web app server in background and run Nginx
# Run WAS in background gunicorn -k uvicorn.workers.UvicornWorker main:app --bind <IP_ADDRESS>:${MAIN_PORT} -w ${MAIN_WORKER} --timeout ${MAIN_TIMEOUT} --daemon # Insert env-variables in .conf file and run nginx envsubst < /opt/nginx.conf > /etc/nginx/conf.d/default.conf && nginx -g 'daemon off;'


To add cell template in data grid add <ng-template> in html file and get that template as TemplateRef<any> in component
Now set that template reference in cellTemplate property in column definations
In HTML file:{{htmlText}}
{{templateText}}
{{columnText}}


. ____ . ____________________________ |/ \| | | [| ♥ ♥ |] | ChatBox by vicky | |___==___| / © Prabhu Vignesh Kumar 2017 | |____________________________|
Hi There!!
Exit Chat


Re: New Models
Posted: Mon Mar 30, 2009 3:20 pm
Are there any items (ideas) in particular that anyone has? I'm going to see if I can recruit my wife to start mocking up some designs. Shes quite the artist.
Game Development and More
http://unseenstudios.com/community/
http://unseenstudios.com/community/viewtopic.php?f=25&t=1394
thadiusofx3 wrote:I just got promoted at work so im having to work a lot of overtime lately, im gonna try to work on some models either tonight or tomorrow when im off (half the day anyway)
I'm also learning some new techniques for models that im gonna try to improve on some more.
It's kinda hard to work on this in your spare time when you barely have any lol


This tutorial covers grouping with values other than count shown in the group header, and with edit enabled.
We create a custom columnsProcessor to override the default aggregation that grouping sets, including setting a custom aggregation function so that we can aggregate data from a different column than the one we're on.
We turn on the ability to select group headers, and write a callback on the selection event to select all children of the selected rowHeader.


This is an ACSR Championship.
That means that when you sign up for this Championship, the following details will be sent to ACSR:
- Your Name, as provided in the form above (anonymised if possible, e.g. "Alan Turing" would become "Alan T.")
- An anonymized version of your Steam GUID
- All Race, Qualifying and Practice results and Championship Positions
By signing up to this Championship, you agree that this data can be shared with ACSR.
{{ if or $championship.EnableACSRSkillGate $championship.EnableACSRSafetyGate }}
You need to meet the following minimum ACSR ratings to join this Championship:
{{ if $championship.EnableACSRSkillGate }}
{{ $championship.ACSRSkillGate }}
{{ end }}
{{ if $championship.EnableACSRSafetyGate }}
{{ $championship.ACSRSafetyGate }}
{{ end }}
Your Rating:
Unknown! Please enter your GUID in the Steam GUID input above!
{{ end }}


All photos are either under a Creative Commons license or were marked as shareable by their creators. Comments? I'm @lealeelu on Twitter. Complaints? Maybe you need another fat cat. This site is inspired by @yaypie's Emergency Kitten.


[§393-22] Exemption of followers of certain teachings or beliefs. This chapter shall not apply to any individual who pursuant to the teachings, faith, or belief of any group, depends for healing upon prayer or other spiritual means. [L 1974, c 210, pt of §1]


It is a homepage that summarizes what I want to introduce. 'Ama et fac quod vis' is my favorite sentence,this mean is Love and do what you want. The video of the banner is a game video that I and my team members worked on. I have more projects on my homepage. Have fun!


I know this is your first day, so you must be a little confused. Your job is to run some tests on the Mr. Rogerbots as they come down the assembly line. They will ask you for your name, and a whole number. Last name is optional, of course. They shoud be able to count from zero to your number, and in reverse! Fair warning, any number that contains one, two, or three might make them buzz with glee!


I love to develop unique and effective software. I have experience in various programming languages. Including object oriented programming languages like Java, C++ and C#


File Upload widget with multiple file selection, drag&drop support, progress bar and preview images for jQuery.
Supports cross-domain, chunked and resumable file uploads.
Works with any server-side platform (Google App Engine, PHP, Python, Ruby on Rails, Java, etc.) that supports standard HTML form file uploads.


{% extends "email_base.html" %} {% block salutation %}
Dear {{guest.first_name}},
{% endblock %} {% block content %}Your invite code for wedding.example.org is: {{ guest.invitee.invite_code }}
You can update your RSVP and other information by going to:
http://wedding.example.org/rsvp/{{guest.invitee.invite_code}}/
Best wishes,
Alyssa and Ben
{% endblock %}


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for a safe space for young refugees to rest
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{{ data.paragraphOne }}
{{ data.paragraphTwo }}
i love me.
i love 1D they are the best.
my life is really crazy.
one thing about my life is that i have a wonderful family.
{{ data.paragraphOne }}
{{ data.paragraphTwo }}
{{ data.paragraphThree }}
{{ data.paragraphFour }}


THE SUICIDE'S SPEARMAN.
A FAMILY of the name of Spearman has lived in Cornwall for many ages, their native centre having been somewhere between Ludgvan and St Ives.
Years long ago, an unfortunate man, weary of life, destroyed himself; and the rude laws of a remote age, carrying out, as they thought, human punishments even after death, decreed that the body should be buried at the four cross-roads, and quicklime poured on the corpse.
Superstition stepped in, and somewhat changed the order of burial. To prevent the dead man from "walking," and becoming a terror to all his neighbours, the coffin was to be turned upside down, and a spear was to be driven through it and the body, so as to pin it to the ground.
It was with some difficulty that a man could be found to perform this task. At length, however, a blacksmith undertook it. He made the spear; and after the coffin was properly placed, he drove his spear-headed iron bar through it. From that day he was called "the spearman," and his descendants have never lost the name.
In making a new road not many years since, the coffin and spear were found, and removed. From that time several old men and women have declared that the self-murderer "walks the earth."


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Urban and Suburban Employment: Bar Chart Comparison
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WITNESS LIST Finance Committee October 18, 2004 - 9:00A Article II ON: Berndt, Trey (Health and Human Services Commission), Austin, TX Carruth, Lisa Director, System Forecasting (Health and Human Services Commission), Austin, TX Cook, David Budget (Department of Aging and Disability Services), Austin, TX Hawkins, Albert Executive Commissioner (Health and Human Services Commission), Austin, TX Henderson, Tracy Chief Financial Officer (Health and Human Services Commission), Austin, TX Hine, Jim Commissioner (Department of Aging and Disability Services), Austin, TX Horn, Adelaide Deputy Commissioner (Department of Aging and Disability Services), Austin, TX LeBrun, Aurora F. Associate Commissioner (Health and Human Services Commission), Austin, TX Suehs, Thomas Executive Deputy Commissioner (Health and Human Services Commission), Austin, TX Taylor, Gordon Chief Financial Officer (Department of Aging and Disability Services), Austin, TX


Waits for selected processors to complete processing of all pending messages in their mailboxes.
Waits for selected processors to complete processing of all pending messages in their mailboxes.
ids of registered processors to wait for. Default value is the set of all registered processor ids.
maximum duration to wait for processing to complete.
Creates and registers a Channel.
Creates and registers a Channel. The channel is
registered under the id specified by props.id
. If props.name
is defined it is also
registered under that name.
channel configuration object.
Channel ref factory.
a channel ref.
if name
is defined and already in use
in the underlying actor system.
Map of registered Channels.
Map of registered Channels. Mapping key is the channel id.
Enables the channel registered under channelId
and starts delivery of pending messages.
Enables all registered channels and starts delivery of pending messages.
Journal for this extension.
Map of registered named Channels.
Map of registered named Channels. Mapping key is the channel name.
Registers an Eventsourced processor.
Registers an Eventsourced processor.
This method obtains the id from the created processor with a blocking operation.
Use the overloaded processorOf(ProcessorProps)
method if you want to avoid
blocking.
actor ref configuration object.
optional processor name.
Eventsourced ref factory.
a processor ref.
if name
is defined and already in use
in the underlying actor system.
Registers an Eventsourced processor.
Registers an Eventsourced processor.
processor configuration object.
a processor ref.
if props.name
is defined and already
in use in the underlying actor system.
Map of registered Eventsourced processors.
Map of registered Eventsourced processors. Mapping key is the processor id.
Recovers selected processors and all channels registered at this extension by first
calling replay(f)
and then deliver()
.
Recovers selected processors and all channels registered at this extension by first
calling replay(f)
and then deliver()
.
This method waits for replayed messages being added to processor mailboxes but does not wait for replayed input messages being processed. However, any new message sent to any of the selected processors, after this method successfully returned, is guaranteed to be processed after the replayed event messages.
Clients that want to wait for replayed messages being processed should call the
awaitProcessing
method after this method successfully returned.
function called for each processor id. If the function returns None
no message replay will be done for that processor. If it returns Some(snr)
message replay will start from sequence number snr
for that processor.
wait for the specified duration for the replay to complete.
if replay doesn't complete within the specified duration.
Recovers all processors and channels registered at this extension by first
calling replay(_ => Some(0))
and then deliver()
.
Recovers all processors and channels registered at this extension by first
calling replay(_ => Some(0))
and then deliver()
. Replay is done with no
lower bound (i.e. with all messages in the journal).
This method waits for replayed messages being added to processor mailboxes but does not wait for replayed input messages being processed. However, any new message sent to any of the selected processors, after this method successfully returned, is guaranteed to be processed after the replayed event messages.
Clients that want to wait for replayed messages being processed should call the
awaitProcessing
method after this method successfully returned.
wait for the specified duration for the replay to complete.
if replay doesn't complete within the specified duration.
Replays input messages to selected processors.
Replays input messages to selected processors. This method waits for replayed messages being added to processor mailboxes but does not wait for replayed input messages being processed. However, any new message sent to any of the selected processors, after this method successfully returned, is guaranteed to be processed after the replayed event messages.
Clients that want to wait for replayed messages being processed should call the
awaitProcessing
method after this method successfully returned.
function called for each processor id. If the function returns None
no message replay will be done for that processor. If it returns Some(snr)
message replay will start from sequence number snr
for that processor.
wait for the specified duration for the replay to complete.
if replay doesn't complete within the specified duration.
Event-sourcing extension for Akka. Used by applications to create and register Eventsourced processors and event message Channels and to recover them from journaled event Messages.


| Home · Pages · Index · Overviews |
All Mylib Classes and ModulesMylib Core ModuleSystem-wide types and routines. Generic Class Routines ModuleThe operations common to every class. Array ClassN-dimensional arrays over scalar data. Slice ClassA sub-array of an Array defined by any two corner coordinates. Frame ClassA hyper-rectangular region of interest that can be moved over an Array. AForm ClassAn Array, a Slice, or a Frame. Connectivity ModuleTraversals of n-dimensional arrays and general flood fill operations. Region ClassA compact encoding of any connected collection of voxels. Histogram ClassFlexible statistical analyses of the values in any AForm object. Draw ModuleRoutines that paint shapes and Mylib objects onto an Array or Slice. Image I/O ModuleI/O of Tiff-encoded multi-channel images and stacks. Tiff ClassDirect I/O of individual multi-channel Tiff Image File Descriptors (IFDs). Correlation and Regression ModuleFunctions for correlations and regressions over AForm objects. Convolver ClassDirect convolution of a filter at any location within an Array. Filters ModuleEfficient routines for filtering images with common filters. Distance Transform ModuleDistance transforms and Voronoi, Delauney and geodesic partitioning based there upon. Level_Tree ClassA tree of all the level sets in an Array or Slice. Partition ClassA graph model of a partition and routines to progressively collapse said. Watershed ModuleRoutines to produce a watershed partition of an image. Shortest Paths ModuleShortest paths routines SWC_Tree ClassSupport for the .swc tree format: a piece-wise segment model of neurons. Linear Algebra ModuleMatrix arithmetic including inversion. LU_Factor ClassAn LU decomposition of a matrix: inversion, determinants, linear equations. Band_Factor ClassA sparse LU decompositions of tri- and penta-diagonal matrices. Function Minimization ModuleMinimization of functions of one or more variables, with and without a derivative/gradient. Root Finding ModuleRoot finding of a unary function with and without a derivative. Fast Fourier Transform ModuleFast fourier transforms, convolution, correlation, and normalized correlation. CDF ClassGenerators for random variables from different common distributions. Hash_Table ClassA classic hash table that holds a set of strings and maps them to consecutive integer IDs. SVG Drawing ModuleA module for generating 2D SVG drawings displayable on the www and editable with Inkscape. System Utilities & Command Line Interface ModuleA flexible command line processing suite and guarded system utilities. |


Match Play. Red trails 2-3 to 5. Should Red double? If doubled, should White take?
pips Red=99 White=113
(CorrectAnswer= 0/0, ErrorScore= 0)
A difficult problem: Red leads in the race and can release one checker from his 17-pt when two of his checkers will then be holding four of White's.
For money it would be a huge mistake to double as the position has very low volatility and other than 33 and 44 Red has no potential market losers. The match score has some influence however because getting to 4-3 Crawford is a big advantage for Red.
However, the very low volatility and the very low gammon percentage mean that Red should wait. This position actually occurred at UK Open with Red being Chris Rogers and White being Mochy. I think (but can't prove) that the disparity in skill makes the double reasonable rather than an error which is how XG rates it.
Chris rolled 51 (10/5, 6/5) and then Mochy rolled 62 which he correctly played 13/11, 13/7 as then if Red hits with 33 he has to break his home board. Chris missed the shot and after a long battle Chris misplayed a vital 41 in the bear-off, got hit, and Mochy won the game and match.
For money it would be a huge mistake to double as the position has very low volatility and other than 33 and 44 Red has no potential market losers. The match score has some influence however because getting to 4-3 Crawford is a big advantage for Red.
However, the very low volatility and the very low gammon percentage mean that Red should wait. This position actually occurred at UK Open with Red being Chris Rogers and White being Mochy. I think (but can't prove) that the disparity in skill makes the double reasonable rather than an error which is how XG rates it.
Chris rolled 51 (10/5, 6/5) and then Mochy rolled 62 which he correctly played 13/11, 13/7 as then if Red hits with 33 he has to break his home board. Chris missed the shot and after a long battle Chris misplayed a vital 41 in the bear-off, got hit, and Mochy won the game and match.
1. Cubeful 2-ply 8/2*/1* Eq.: -0.119 0.494 0.208 0.006 - 0.506 0.133 0.005 2. Cubeful 2-ply 21/14 Eq.: -0.165 (-0.046) 0.501 0.155 0.007 - 0.499 0.152 0.005 3. Cubeful 2-ply 13/6 Eq.: -0.256 (-0.138) 0.454 0.155 0.006 - 0.546 0.124 0.004 4. Cubeful 2-ply 13/7 8/7 Eq.: -0.259 (-0.141) 0.458 0.153 0.006 - 0.542 0.138 0.004 5. Cubeful 2-ply 8/7 8/2* Eq.: -0.298 (-0.179) 0.449 0.148 0.005 - 0.551 0.150 0.005


About Me
Hey Everyone,
i am Manish Aggarwal, Seeking a challenging and successful career in Data Science , full stack and related technologies like predictive modelling, data cleaning, data processing, frontend backend development to solve challenging business problems.
- Favourite Novel - Demons in My Mind.
- Favourite Sports - Chess , Cricket.
- Favourite Movie - Interstellar.
Skills
Work
Full stack dev intern | Newton School(May 2021 - Present)
- Learnt Data Structures and Algorithms
- Developed Full stack web apps.
Data analysis and Machine learning engg | The Intern Academy(June 2021- July 2021)
- Worked on classification models and increase the accuracy of the model from 87% to 91.
- Built image classification model.
- Built a model in the healthcare domain.
Freelancer | fiverr(Jan 2021- August 2021)
- experience in working with different timezones and handling international clients.
- making business dashboards using google data studio..
- worked on increasing the performance of the model and data visualization.
Projects
Potato Disease classification
A classification model based on Deep learning Algorithms to predict Disease in potato leaf.
View DemoSource Code
Flight Price Prediction
classification model based on machine learning Algorithms to predict Ticket price from Source to Destination.
View DemoSource Code


This is a very simple monitoring panel for interacting with I2P and monitoring I2P statistics. It can stop, or restart an I2P router, as well as provide concise output about I2P router status from I2PControl. It depends on the presence of an I2P router implementing the i2pcontrol jsonrpc interface.
To enable jsonrpc on the Java I2P router, go to this the webapps config page:
http://localhost:7657/configwebapps
and
enable the
jsonrpc
app as seen in the screenshot below:
I don’t have a Mac, mine bit the dust. I need help creating a Mac package of this. Please, if you want a Mac version of this application and have Mac packaging experience, create an issue so we can work together to figure out how to support Mac users best.
MIT License
Copyright (c) 2020 idk
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
 IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
Hide license


Your users are no longer sitting at their desktops, with a wire connecting them to the internet.
They are visiting your site from a phone in an elevator, from their tablet on the subway, or on their laptop while they sit cramped into seat 25 E.
This is why modern browsers support ServiceWorkers, a new technology which lets you serve your content to your users, even when they are offline.
UpUp is a free, open source project which makes using this modern magic as simple as calling one command.
<script src="/upup.min.js"></script>
<script>
UpUp.start({
'content-url': 'offline.html' // show this page to offline users
});
</script>
While easy to pick up, UpUp is powerful enough to support anything from showing simple messages, to making fully functional single page applications available offline, with data customized for each of your users.
UpUp is a free, open source, community effort.
Please help us start the Offline First revolution:


Consuming External TCP Services
Egress rules for TCP traffic
In my previous blog post, Consuming External Web Services, I described how external services can be consumed by in-mesh Istio applications via HTTPS. In this post, I demonstrate consuming external services over TCP. I use the Istio Bookinfo sample application, the version in which the book ratings data is persisted in a MySQL database. I deploy this database outside the cluster and configure the ratings microservice to use it. I define an egress rule to allow the in-mesh applications to access the external database.
Bookinfo sample application with external ratings database
First, I set up a MySQL database instance to hold book ratings data, outside my Kubernetes cluster. Then I modify the Bookinfo sample application to use my database.
Setting up the database for ratings data
For this task I set up an instance of MySQL. You can use any MySQL instance; I use Compose for MySQL. I use mysqlsh
(MySQL Shell) as a MySQL client to feed the ratings data.
-
To initialize the database, I run the following command entering the password when prompted. The command is performed with the credentials of the
admin
user, created by default by Compose for MySQL.$ curl -s https://raw.githubusercontent.com/istio/istio/release-0.8/samples/bookinfo/src/mysql/mysqldb-init.sql | \ mysqlsh --sql --ssl-mode=REQUIRED -u admin -p --host <the database host> --port <the database port>
OR
When using the
mysql
client and a local MySQL database, I would run:$ curl -s https://raw.githubusercontent.com/istio/istio/release-0.8/samples/bookinfo/src/mysql/mysqldb-init.sql | \ mysql -u root -p
-
I then create a user with the name bookinfo and grant it SELECT privilege on the
test.ratings
table:$ mysqlsh --sql --ssl-mode=REQUIRED -u admin -p --host <the database host> --port <the database port> \ -e "CREATE USER 'bookinfo' IDENTIFIED BY '<password you choose>'; GRANT SELECT ON test.ratings to 'bookinfo';"
OR
For
mysql
and the local database, the command would be:$ mysql -u root -p -e \ "CREATE USER 'bookinfo' IDENTIFIED BY '<password you choose>'; GRANT SELECT ON test.ratings to 'bookinfo';"
Here I apply the principle of least privilege. This means that I do not use my admin user in the Bookinfo application. Instead, I create a special user for the Bookinfo application , bookinfo, with minimal privileges. In this case, the bookinfo user only has the
SELECT
privilege on a single table.After running the command to create the user, I will clean my bash history by checking the number of the last command and running
history -d <the number of the command that created the user>
. I don't want the password of the new user to be stored in the bash history. If I'm usingmysql
, I'll remove the last command from~/.mysql_history
file as well. Read more about password protection of the newly created user in MySQL documentation. -
I inspect the created ratings to see that everything worked as expected:
$ mysqlsh --sql --ssl-mode=REQUIRED -u bookinfo -p --host <the database host> --port <the database port> \ -e "select * from test.ratings;" Enter password: +----------+--------+ | ReviewID | Rating | +----------+--------+ | 1 | 5 | | 2 | 4 | +----------+--------+
OR
For
mysql
and the local database:$ mysql -u bookinfo -p -e "select * from test.ratings;" Enter password: +----------+--------+ | ReviewID | Rating | +----------+--------+ | 1 | 5 | | 2 | 4 | +----------+--------+
-
I set the ratings temporarily to 1 to provide a visual clue when our database is used by the Bookinfo ratings service:
$ mysqlsh --sql --ssl-mode=REQUIRED -u admin -p --host <the database host> --port <the database port> \ -e "update test.ratings set rating=1; select * from test.ratings;" Enter password: +----------+--------+ | ReviewID | Rating | +----------+--------+ | 1 | 1 | | 2 | 1 | +----------+--------+
OR
For
mysql
and the local database:$ mysql -u root -p -e "update test.ratings set rating=1; select * from test.ratings;" Enter password: +----------+--------+ | ReviewID | Rating | +----------+--------+ | 1 | 1 | | 2 | 1 | +----------+--------+
I used the admin user (and root for the local database) in the last command since the bookinfo user does not have the UPDATE privilege on the
test.ratings
table.
Now I am ready to deploy a version of the Bookinfo application that will use my database.
Initial setting of Bookinfo application
To demonstrate the scenario of using an external database, I start with a Kubernetes cluster with Istio installed. Then I deploy the Istio Bookinfo sample application. This application uses the ratings microservice to fetch book ratings, a number between 1 and 5. The ratings are displayed as stars for each review. There are several versions of the ratings microservice. Some use MongoDB, others use MySQL as their database.
The example commands in this blog post work with Istio 0.3+, with or without Mutual TLS enabled.
As a reminder, here is the end-to-end architecture of the application from the Bookinfo Guide.
Use the database for ratings data in Bookinfo application
-
I modify the deployment spec of a version of the ratings microservice that uses a MySQL database, to use my database instance. The spec is in
samples/bookinfo/kube/bookinfo-ratings-v2-mysql.yaml
of an Istio release archive. I edit the following lines:- name: MYSQL_DB_HOST value: mysqldb - name: MYSQL_DB_PORT value: "3306" - name: MYSQL_DB_USER value: root - name: MYSQL_DB_PASSWORD value: password
I replace the values in the snippet above, specifying the database host, port, user, and password. Note that the correct way to work with passwords in container's environment variables in Kubernetes is to use secrets. For this example task only, I write the password directly in the deployment spec. Do not do it in a real environment! I also assume everyone realizes that
"password"
should not be used as a password… -
I apply the modified spec to deploy the version of the ratings microservice, v2-mysql, that will use my database.
$ kubectl apply -f <(istioctl kube-inject -f @samples/bookinfo/kube/bookinfo-ratings-v2-mysql.yaml@) deployment "ratings-v2-mysql" created
-
I route all the traffic destined to the reviews service to its v3 version. I do this to ensure that the reviews service always calls the ratings service. In addition, I route all the traffic destined to the ratings service to ratings v2-mysql that uses my database. I add routing for both services above by adding two route rules. These rules are specified in
samples/bookinfo/kube/route-rule-ratings-mysql.yaml
of an Istio release archive.$ istioctl create -f @samples/bookinfo/kube/route-rule-ratings-mysql.yaml@ Created config route-rule/default/ratings-test-v2-mysql at revision 1918799 Created config route-rule/default/reviews-test-ratings-v2 at revision 1918800
The updated architecture appears below. Note that the blue arrows inside the mesh mark the traffic configured according to the route rules we added. According to the route rules, the traffic is sent to reviews v3 and ratings v2-mysql.
Note that the MySQL database is outside the Istio service mesh, or more precisely outside the Kubernetes cluster. The boundary of the service mesh is marked by a dashed line.
Access the webpage
Let's access the webpage of the application, after determining the ingress IP and port.
We have a problem… Instead of the rating stars, the message “Ratings service is currently unavailable” is currently displayed below each review:
As in Consuming External Web Services, we experience graceful service degradation, which is good. The application did not crash due to the error in the ratings microservice. The webpage of the application correctly displayed the book information, the details, and the reviews, just without the rating stars.
We have the same problem as in Consuming External Web Services, namely all the traffic outside the Kubernetes cluster, both TCP and HTTP, is blocked by default by the sidecar proxies. To enable such traffic for TCP, an egress rule for TCP must be defined.
Egress rule for an external MySQL instance
TCP egress rules come to our rescue. I copy the following YAML spec to a text file (let's call it egress-rule-mysql.yaml
) and edit it to specify the IP of my database instance and its port.
apiVersion: config.istio.io/v1alpha2
kind: EgressRule
metadata:
name: mysql
namespace: default
spec:
destination:
service: <MySQL instance IP>
ports:
- port: <MySQL instance port>
protocol: tcp
Then I run istioctl
to add the egress rule to the service mesh:
$ istioctl create -f egress-rule-mysql.yaml
Created config egress-rule/default/mysql at revision 1954425
Note that for a TCP egress rule, we specify tcp
as the protocol of a port of the rule. Also note that we use an IP of the external service instead of its domain name. I will talk more about TCP egress rules below. For now, let's verify that the egress rule we added fixed the problem. Let's access the webpage and see if the stars are back.
It worked! Accessing the web page of the application displays the ratings without error:
Note that we see a one-star rating for both displayed reviews, as expected. I changed the ratings to be one star to provide us with a visual clue that our external database is indeed being used.
As with egress rules for HTTP/HTTPS, we can delete and create egress rules for TCP using istioctl
, dynamically.
Motivation for egress TCP traffic control
Some in-mesh Istio applications must access external services, for example legacy systems. In many cases, the access is not performed over HTTP or HTTPS protocols. Other TCP protocols are used, such as database-specific protocols like MongoDB Wire Protocol and MySQL Client/Server Protocol to communicate with external databases.
Note that in case of access to external HTTPS services, as described in the Control Egress TCP Traffic task, an application must issue HTTP requests to the external service. The Envoy sidecar proxy attached to the pod or the VM, will intercept the requests and open an HTTPS connection to the external service. The traffic will be unencrypted inside the pod or the VM, but it will leave the pod or the VM encrypted.
However, sometimes this approach cannot work due to the following reasons:
-
The code of the application is configured to use an HTTPS URL and cannot be changed
-
The code of the application uses some library to access the external service and that library uses HTTPS only
-
There are compliance requirements that do not allow unencrypted traffic, even if the traffic is unencrypted only inside the pod or the VM
In this case, HTTPS can be treated by Istio as opaque TCP and can be handled in the same way as other TCP non-HTTP protocols.
Next let's see how we define egress rules for TCP traffic.
Egress rules for TCP traffic
The egress rules for enabling TCP traffic to a specific port must specify TCP
as the protocol of the port. Additionally, for the MongoDB Wire Protocol, the protocol can be specified as MONGO
, instead of TCP
.
For the destination.service
field of the rule, an IP or a block of IPs in CIDR notation must be used.
To enable TCP traffic to an external service by its hostname, all the IPs of the hostname must be specified. Each IP must be specified by a CIDR block or as a single IP, with each block or IP in a separate egress rule.
Note that all the IPs of an external service are not always known. To enable TCP traffic by IPs, as opposed to the traffic by a hostname, only the IPs that are used by the applications must be specified.
Also note that the IPs of an external service are not always static, for example in the case of CDNs. Sometimes the IPs are static most of the time, but can be changed from time to time, for example due to infrastructure changes. In these cases, if the range of the possible IPs is known, you should specify the range by CIDR blocks (even by multiple egress rules if needed). If the range of the possible IPs is not known, egress rules for TCP cannot be used and the external services must be called directly, circumventing the sidecar proxies.
Relation to mesh expansion
Note that the scenario described in this post is different from the mesh expansion scenario, described in the
Integrating Virtual Machines guide. In that scenario, a MySQL instance runs on an external
(outside the cluster) machine (a bare metal or a VM), integrated with the Istio service mesh. The MySQL service becomes a first-class citizen of the mesh with all the beneficial features of Istio applicable. Among other things, the service becomes addressable by a local cluster domain name, for example by mysqldb.vm.svc.cluster.local
, and the communication to it can be secured by
mutual TLS authentication. There is no need to create an egress rule to access this service; however, the
service must be registered with Istio. To enable such integration, Istio components (Envoy proxy, node-agent, istio-agent) must be
installed on the machine and the Istio control plane (Pilot, Mixer, CA) must be accessible from it. See the
Istio Mesh Expansion instructions for more details.
In our case, the MySQL instance can run on any machine or can be provisioned as a service by a cloud provider. There is no requirement to integrate the machine with Istio. The Istio control plane does not have to be accessible from the machine. In the case of MySQL as a service, the machine which MySQL runs on may be not accessible and installing on it the required components may be impossible. In our case, the MySQL instance is addressable by its global domain name, which could be beneficial if the consuming applications expect to use that domain name. This is especially relevant when that expected domain name cannot be changed in the deployment configuration of the consuming applications.
Cleanup
-
Drop the test database and the bookinfo user:
$ mysqlsh --sql --ssl-mode=REQUIRED -u admin -p --host <the database host> --port <the database port> \ -e "drop database test; drop user bookinfo;"
OR
For
mysql
and the local database:$ mysql -u root -p -e "drop database test; drop user bookinfo;"
-
Remove the route rules:
$ istioctl delete -f @samples/bookinfo/kube/route-rule-ratings-mysql.yaml@ Deleted config: route-rule/default/ratings-test-v2-mysql Deleted config: route-rule/default/reviews-test-ratings-v2
-
Undeploy ratings v2-mysql:
$ kubectl delete -f <(istioctl kube-inject -f @samples/bookinfo/kube/bookinfo-ratings-v2-mysql.yaml@) deployment "ratings-v2-mysql" deleted
-
Delete the egress rule:
$ istioctl delete egressrule mysql -n default Deleted config: egressrule mysql
Future work
In my next blog posts, I will show examples of combining route rules and egress rules, and also examples of accessing external services via Kubernetes ExternalName services.
Conclusion
In this blog post, I demonstrated how the microservices in an Istio service mesh can consume external services via TCP. By default, Istio blocks all the traffic, TCP and HTTP, to the hosts outside the cluster. To enable such traffic for TCP, TCP egress rules must be created for the service mesh.
What's next
To read more about Istio egress traffic control, see Control Egress Traffic Task.


Chapter 9 Pandas
This module introduces the Python Data Analysis library pandas
—a set of modules, functions, and classes used to for easily and efficiently performing data analysis—panda
’s speciality is its highly optimized performance when working with large data sets. pandas
is the most common library used with Python for Data Science (and mirrors the R
language in many ways, allowing programmers to easily move between the two). In this module, we will discuss the two main data structures used by pandas
(Series and DataFrames) and how to use them to organize and work with data.
Contents
- Resources
- Setup
- Series
- Series Operations and Methods
- Accessing Series
- Data Frames
- DataFrame Operations and Methods
- Accessing DataFrames
9.1 Resources
- 10 minutes to pandas (pandas docs) a basic set of examples
- Tutorials (pandas docs) a list and guide to various tutorials (of mixed quality)
- Intro to Data Structure (pandas docs)
- Essential Basic Functionality (pandas docs) not really basic, but a complete set of examples
- Pandas. Data Processing (Data Analysis in Python)
- pandas Foundations (DataCamp)
9.2 Setup
pandas
is a third-party library (not built into Python!), but is included by default with Anaconda and so can be imported directly. Additionally, Pandas is built on top of the numpy
scientific computing library which supports highly optimized mathematical operations. Thus many pandas
operations involve working with numpy
data structures, and the pandas
library requires numpy
(also included in Anaconda) to also be imported:
# import libraries
import pandas as pd # standard shortcut names
import numpy as np
We usually
import
the module and reference types and methods using dot notation, rather than importing them into the global namespace.Note that this module will focus primarily on
pandas
, leavingnumpy
-specific data structures and functions for the reader to explore.
9.3 Series
The first basic pandas
data structure is a Series. A Series represents a one-dimensional ordered collection of values, making them somewhat similar to a regular Python list. However, elements can also be given labels (called the index), which can be non-numeric values, similar to a key in a Python dictionary. This makes a Series somewhat like an ordered dictionary—one that supports additional methods and efficient data-processing behaviors.
Series can be created using the Series()
function (a constructor for instances of the class):
# create a Series from a list
number_series = pd.Series([1, 2, 2, 3, 5, 8])
print(number_series)
produces
0 1
1 2
2 2
3 3
4 5
5 8
dtype: int64
Printing a Series will display it like a table: the first value in each row is the index (label) of that element, and the second is the value of the element in the Series.
- Printing will also display the type of the elements in the Series. All elements in the Series will be treated as “same” type—if you create a Series from mixed elements (e.g., numbers and strings), the type will be the a generic
object
. In practice, we almost always create Series from a single type.
If we create a Series from a list, each element will be given an index (label) that is that values’s index in the list. We can also create a Series from a dictionary, in which case the keys will be used as the index labels:
# create a Series from a dictionary
age_series = pd.Series({'sarah':42, 'amit':35, 'zhang':13})
print(age_series)
amit 35
sarah 42
zhang 13
dtype: int64
- Note that the Series is automatically sorted by the keys of the dictionary! This means that the order of the elements in the Series will always be the same for a given dictionary (which cannot be said for the dictionary items themselves).
9.3.1 Series Operations and Methods
The main benefit of Series (as opposed to normal lists or dictionaries) is that they provide a number of operations and methods that make it easy to consider and modify the entire Series, rather than needing to worth with each element individually. In a way, the functions include built-in mapping, reducing, and filtering style operations.
In particular, basic operators (whether math operators such as +
and -
, or relational operators such as >
or ==
) function as vectorized operations, meaning that they are applied to the entire Series member-wise: the operation is applied to the first element in the Series, then the second, then the third, and so forth:
sample = pd.Series(range(1,6)) # Series of numbers from 1 to 5 (6 is excluded)
result = sample + 4 # add 4 to each element (produces new Series)
print(result)
# 0 5
# 1 6
# 2 7
# 3 8
# 4 9
# dtype: int64
is_greater_than_3 = sample > 3 # compare each element
print(is_greater_than_3)
# 0 False
# 1 False
# 2 False
# 3 True # note index and value are not the same
# 4 True
# dtype: bool
- Having a Series operation apply to a scalar (a single value) is referred to as broadcasting. The idea is that the smaller “set” of elements (e.g., a single value) is broadcast so that it has a comparible size, thereby allowing different “sized” data structures to interact. Technically, operating on a Series with a scalar is actually a specific case of operating on it with another Series!
If the second operand is another Series, then mathematical and relational operations are still applied member-wise, with the elements of each operand being “matched” by their index label. This means that for most Series whose indices are
s1 = pd.Series([2, 2, 2, 2, 2])
s2 = pd.Series([1, 2, 3, 4, 5])
# examples of operations (list only includes values)
list(s1 + s2) # [3, 4, 5, 6, 7]
list(s1 / s2) # [2.0, 1.0, 0.66666666666666663, 0.5, 0.40000000000000002]
list(s1 < s2) # [False, False, True, True, True]
# add a Series to itself (why not?)
list(s2 + s2) # [2, 4, 6, 8, 10]
# perform more advanced arithmetic!
s3 = (s1 + s2) / (s1 + s1)
list(s3) # [0.75, 1.0, 1.25, 1.5, 1.75]
And note that these operations will be fast, even for very large Series, allowing for effective data manipulations.
pandas
Series also include a number of methods for inspecting and manipulating the data. Some useful examples (not comprehensive):
| Function | Description |
|---|---|
index |
an attribute; the sequence of index labels (convert to a list to use) |
head(n) |
returns a Series containing only the first n elements |
tail(n) |
returns a Series containing only the last n elements |
any() |
returns whether ANY of the elements are True (or “truthy”) |
all() |
returns whether ALL of the elements are True (or “truthy”) |
mean() |
returns the statistical mean of the elements in the Series |
std() |
returns the standard deviation of the elements in the Series |
describe() |
returns a Series of descriptive statistics |
idxmax() |
returns the index label of the element with the max value |
Series support many more methods as well: see the full documentation for a complete list.
One particularly useful method to mention is the apply()
method. This method is used to apply a particular callback function to each element in the series. This is a mapping operation, similar to what we’ve done with the map()
function:
def square(n): # a function that squares a number
return n**2
number_series = pd.Series([1,2,3,4,5]) # an initial series
square_series = number_series.apply(square)
list(square_series) # [1, 4, 9, 16, 25]
# can also apply built-in functions
import math
sqrt_series = number_series.apply(math.sqrt)
list(sqrt_series) # [1.0, 1.4142135623730951, 1.7320508075688772, 2.0, 2.2360679774997898]
# pass additional arguments as keyword args (or `args` for a single argument)
cubed_series = number_series.apply(math.pow, args=(3,)) # call math.exp(n, 3) on each
list(cubed_series) # [1.0, 8.0, 27.0, 64.0, 125.0]
9.3.2 Accessing Series
Just like lists and dictionaries, elements in a Series can be accessed using bracket notation, putting the index label inside the brackets:
number_series = pd.Series([1, 2, 2, 3, 5, 8])
age_series = pd.Series({'sarah':42, 'amit':35, 'zhang':13})
# get the 1th element from the number_series
number_series[1] # 2
# get the 'sarah' element from age_series
age_series['amit'] # 35
# get the 0th element from age_series
# (Series are ordered, so can be accessed positionally)
age_series[0] # 42
Note that the returned values are not technically basic int
or float
or string
types, but are rather specific numpy
objects that work almost identically to their normal type (but with some additional optimization).
You can also use list-style slices using the colon operator (e.g., elements 1:3
).
it is also possible to specify a sequence of indicies (i.e., a list or range or even a Series of indices) to access using bracket notation. This will produce a new Series object that contains only the elements that have those labels:
age_series = pd.Series({'sarah':42, 'amit':35, 'zhang':13})
index_list = ['sarah', 'zhang']
print( age_series[index_list] )
# sarah 42
# zhang 13
# dtype: int64
# using an anonymous variable for the index list (notice the brackets!)
print( age_series[['sarah', 'zhang']] )
# sarah 42
# zhang 13
# dtype: int64
This also means that you can use something like a list comprehension to (or even a Series operation!) to determine which elements to select from a Series!
letter_series = pd.Series(['a','b','c','d','e','f'])
even_numbers = [num for num in range(0,6) if num%2 == 0] # list of even numbers
# get letters with even numbered indices
letter_series[even_numbers] # []
# 0 a
# 2 c
# 4 e
# dtype: object
# in one line (check the brackets!)
letter_series[[num for num in range(0,6) if num%2 == 0]]
Finally, using a sequence of booleans with bracket notatoin will produce a new Series containing the elements whose position corresponds with True
values. This is called boolean indexing.
shoe_sizes = pd.Series([7, 6.5, 4, 11, 8]) # a series of shoe sizes
index_filter = [True, False, False, True, True] # list of which elements to extract
# extract every element in an index that is True
shoe_sizes[index_filter] # has values 7.0, 11.0, 8.0
- In this example, since
index_filter
isTrue
at index 0, 3, and 4, thenshoe_sizes[index_filter]
returns a Series with the elements from index numbers 0, 3, and 4.
This is incredibly powerful because it allows us to easily perform filtering operations on a Series:
shoe_sizes = pd.Series([7, 6.5, 4, 11, 8]) # a series of shoe sizes
big_sizes = shoe_sizes > 6.5 # has values True, False, False, True, True
big_shoes = shoe_sizes[big_sizes] # has values 7, 11, 8
# as one line
big_shoes = shoe_sizes[shoe_size > 6.5]
You can think of the last statement as saying shoe sizes where shoe size is greater than 6.5.
You can include logical operators (“and” and “or”) by using the operators
&
for “and” and|
for “or”. Be sure to wrap each relational expression in()
to enforce order of operations.
While it is perfectly possible to do similar filtering with a list comprehension, the boolean indexing expression can be very simple to read and runs quickly. (This is also the normal style of doing filtering in the R
programming language).
9.4 Data Frames
The most common data structure used in pandas
(more common than Series) is a DataFrame. A DataFrame represents a table, where data is organized into rows and columns. You can think of a DataFrame as being like a Excel spreadsheet or a SQL table.
- We have previously represented tabular data using a list of dictionaries. However, this required us to be careful to make sure that all of the dictionaries shared keys, and did not offer easy ways to interact with the table in terms of its rows or columns. DataFrames give us that functionality!
A DataFrame can also be understood as a dictionary of Series, where each Series represents a column of the table. The keys of this dictionary are the index labels of the columns, while the the index labels of the Series serve as the labels for the row.
- This is distinct from spreadsheets or SQL tables, which are often seen as a collection of observations (rows). Programmatically, DataFrames should primarily be considered as a collection of features (columns), which happen to be sequenced to correspond to observations.
A DataFrame can be created using the DataFrame()
function (a constructor for instances of the class). This function usually takes as an argument dictionary where the values are Series (or values that can be converted into a Series, such as a list or a dictionary):
name_series = pd.Series(['Ada','Bob','Chris','Diya','Emma'])
heights = range(58,63)
weights = [115, 117, 120, 123, 126]
df = pd.DataFrame({'name':name_series, 'height':heights, 'weight':weights})
print(df)
# height name weight
# 0 58 Ada 115
# 1 59 Bob 117
# 2 60 Chris 120
# 3 61 Diya 123
# 4 62 Emma 126
- Although DataFrames variables are often named
df
inpandas
examples, this is not a good variable name. You should use much more descriptive names for your DataFrames (e.g.,person_size_table
) when used in actual programs. - You can specify the order of columns in the table using the
columns
keyword argument, and the order of the rows using theindex
keyword argument.
It is also possible to create a DataFrame directly from a spreadsheet—such as from .csv
file (containing comma sseparated values) by using the pandas.read_csv()
function:
my_dataframe = pd.read_csv('path/to/my/file.csv')
See the IO Tools documentation for details and other file-reading functions.
9.4.1 DataFrame Operations and Methods
Much like Series, DataFrames support a vectorized form of mathematical and relational operators: when the other operand is a scalar, then the operation is applied member-wise to each value in the DataFrame:
# data frame of test scores
test_scores = pd.DataFrame({
'math':[91, 82, 93, 100, 78, 91],
'spanish':[88, 79, 77, 99, 88, 93]
})
curved_scores = test_scores * 1.02 # curve scores up by 2%
print(curved_scores)
# math spanish
# 0 92.82 89.76
# 1 83.64 80.58
# 2 94.86 78.54
# 3 102.00 100.98
# 4 79.56 89.76
# 5 92.82 94.86
print(curved_scores > 90)
# math spanish
# 0 True False
# 1 False False
# 2 True False
# 3 True True
# 4 False False
# 5 True True
It is possible to have both operands be DataFrames. In thiis case the operation is applied member-wise, where values are matched if they have the same row and column label. Note that any value that doesn’t have a pair will instead produce the value NaN
(Not a Number). This is not a normal way of working with DataFrames—it is much more common to access individual rows and columns and work with those (e.g., add make a new column that is the sum of two others); see below for details.
Also like Series, DataFrames objects support a large number of methods, including:
| Function | Description |
|---|---|
index |
an attribute; the sequence of row index labels (convert to a list to use) |
columns |
an attribute; the sequence of column index labels (convert to a list to use) |
head(n) |
returns a DataFrame containing only the first n rows |
tail(n) |
returns a DataFrame containing only the last n rows |
assign(...) |
returns a new DataFrame with an additional column; call as df.assign(new_label=new_column) |
drop(label, row_or_col) |
returns a new DataFrame with the given row or column removed |
mean() |
returns a Series of the statistical means of the values of each column |
all() |
returns a Series of whether ALL the elemnts in each column are True (or “truthy”) |
describe() |
returns a DataFrame whose columns are Series of descriptive statistics for each column in the original DataFrame |
You may notice that many of these methods (e.g., head()
, mean()
, describe()
, any()
) also exist for Series. In fact, most every method that Series support are supported by DataFrames as well. These methods are all applied per column (not per row)—that is, calling mean()
on a DataFrame will calculate the mean of each column in that DataFrame:
df = pd.DataFrame({
'name':['Ada','Bob','Chris','Diya','Emma'],
'height':range(58,63),
'weights':[115, 117, 120, 123, 126]})
df.mean()
# height 60.0
# weights 120.2
# dtype: float64
If the Series method would return a scalar (a single value, as with mean()
or any()
), then the DataFrame method returns a Series whose labels are the column labels, as above. If the Series method instead would return a Series (multiple values, as with head()
or describe()
), then the DataFrame method returns a new DataFrame whose columns are each of the resulting Series:
df = pd.DataFrame({
'name':['Ada','Bob','Chris','Diya','Emma'],
'height':range(58,63),
'weights':[115, 117, 120, 123, 126]})
df.describe()
# height weights
# count 5.000000 5.000000
# mean 60.000000 120.200000
# std 1.581139 4.438468
# min 58.000000 115.000000
# 25% 59.000000 117.000000
# 50% 60.000000 120.000000
# 75% 61.000000 123.000000
# max 62.000000 126.000000
Notice that the
height
column is the result of callingdescribe()
on the DataFrame’sheight
column Series!As a general rule: if you’re expecting one value per column, you’ll get a Series of those values; if you’re expecting multiple values per column, you’ll get a DataFrame of those values.
This also means that you can sometimes “double-call” methods to reduce them further. For example,
df.any()
returns a Series of whether each column contains aTrue
value;df.all().all()
would check if that Series contains allTrue
values (thus checking all columns have allTrue
value, i.e., the entire table is allTrue
values).
9.4.2 Accessing DataFrames
DataFrames make it possible to quickly access individual or a subset of values, though these methods use a variety of syntax structures. For this explanation, refer to the following sample DataFrame initially described above:
# all examples in this section
df = pd.DataFrame({
'name':['Ada','Bob','Chris','Diya','Emma'],
'height':range(58,63),
'weight':[115, 117, 120, 123, 126]
})
print(df)
# height name weight
# 0 58 Ada 115
# 1 59 Bob 117
# 2 60 Chris 120
# 3 61 Diya 123
# 4 62 Emma 126
Since DataFrames are most commonly viewed as a dictionary of columns, it is possible to access them as such using bracket notation (using the index label of the column):
print( df['height'] ) # get height column
# 0 58
# 1 59
# 2 60
# 3 61
# 4 62
# Name: height, dtype: int64
However, it is often more common to refer to individual columns using dot notation, treating each column as an attribute or property of the DataFrame object:
# same results as above
print( df.height ) # get height column
It is also possible to select multiple columns by using a list or sequence inside the bracket notation (similar to selecting multiple values from a Series). This will produce a new DataFrame (a “sub-table”)
# count the brackets carefully!
print( df[['name', 'height']] ) # get name and height columns
# can also select multiple columns with a list of their positions
print( df[[1,2]] ) # get 1st (name) and 2nd (weight) columns
- Watch out though! Specifying a slice (using a colon
:
) will actually select by row position, not column position!
python print( df[0:2] ) # get ROWS 0 through 2 (not inclusive) # height name weight # 0 58 Ada 115 # 1 59 Bob 117
I do not know wherefore this inconsistency, other than “convenience”.
Because DataFrames support multiple indexes, it is possible to use boolean indexing (as with Series), allowing you to filter for rows based the values in their columns:
print( df[ df.height > 60 ] )
# height name weight
# 3 61 Diya 123
# 4 62 Emma 126
- Note that
df.height
is a Series (a column), sodf.height > 60
produces a Series of boolean values (True
andFalse
). This Series is used to determine which rows to return from the DataFrame—each row that corresponds with aTrue
index.
Finally, DataFrames also provide two attributes (properties) used to “quick access” values: loc
, which provides an “index” (lookup table) based on index labels, and iloc
, which provides an “index” (lookup table) based on row and column positions. Each of these “indexes” can be thought of as a dictionary whose values are the individual elements in the DataFrame, and whose keys can therefore be used to access those values using bracket notation. The dictionaries support multiple types of keys (using label-based loc
as an example):
| Key Type | Description | Example |
|---|---|---|
df.loc[row_label] |
An individual value | df.loc['Ada'] (the row labeled Ada ) |
df.loc[row_label_list] |
A list of row labels | df.loc[['Ada','Bob']] (the rows labeled Ada and Bob ) |
df.loc[row_label_slice] |
A slice of row labels | df.loc['Bob':'Diya'] (the rows from Bob to Diya . Note that this is an inclusive slice!) |
df.loc[row_label, col_label] |
A tuple of (row, column) |
df.loc['Ada', 'height'] (the value at row Ada , column height ) |
df.loc[row_label_seq, col_label_seq] |
A tuple of label lists or slices | df.loc['Bob':'Diya', ['height','weight'] (the rows from Bob to Diya with the columns height and weight ) |
Note that the example
df
table doesn’t have row labels beyond0
to4
Using a tuple makes it easy to access a particular value in the table, or a range of values (selecting rows and columns ).
Note that we can also use the boundless slice
:
to refer to “all elements”. So for example:
python df.loc[:, 'height'] # get all rows, 'height' column
This is a basic summary of how to create and access DataFrames; for more detailed usage, additional methods, and specific “recipes”, see the official pandas
documentation.


|
KratosMultiphysics
KRATOS Multiphysics (Kratos) is a framework for building parallel, multi-disciplinary simulation software, aiming at modularity, extensibility, and high performance. Kratos is written in C++, and counts with an extensive Python interface.
|
Variables | |
| ConvDiffSettings = ProjectParameters.ConvectionSolverSettings | |
| domain_size = ProjectParameters.domain_size | |
| model_part = ModelPart("DummyPart"); | |
| gid_mode = GiDPostMode.GiD_PostBinary | |
| multifile = MultiFileFlag.SingleFile | |
| deformed_mesh_flag = WriteDeformedMeshFlag.WriteUndeformed | |
| write_conditions = WriteConditionsFlag.WriteElementsOnly | |
| gid_io = GidIO("PecletTest",gid_mode,multifile,deformed_mesh_flag,write_conditions) | |
| model_part_io = ModelPartIO("PecletTest") | |
| float | conductivity = 0.1 |
| float | velocity = 1.0 |
| float | mesh_name = 0.0 |
| convection_solver = convection_diffusion_solver.CreateSolver(model_part, ProjectParameters) | |
| float | time = 0.0 |
| float | delta_time = 0.1 |
| float | final_time = 10.0 |
| int | step = 0 |
| float | error = 0.0 |
| float | nnodes = 0.0 |
| Temp = node.GetSolutionStepValue(TEMPERATURE) | |
| tuple | aTemp = (1.0-exp(velocity*node.X/conductivity))/(1.0-exp(velocity/conductivity)) |
| tuple PecletTest.aTemp = (1.0-exp(velocity*node.X/conductivity))/(1.0-exp(velocity/conductivity)) |
| float PecletTest.conductivity = 0.1 |
| PecletTest.ConvDiffSettings = ProjectParameters.ConvectionSolverSettings |
| PecletTest.convection_solver = convection_diffusion_solver.CreateSolver(model_part, ProjectParameters) |
| PecletTest.deformed_mesh_flag = WriteDeformedMeshFlag.WriteUndeformed |
| float PecletTest.delta_time = 0.1 |
| PecletTest.domain_size = ProjectParameters.domain_size |
| PecletTest.error = 0.0 |
| float PecletTest.final_time = 10.0 |
| PecletTest.gid_io = GidIO("PecletTest",gid_mode,multifile,deformed_mesh_flag,write_conditions) |
| PecletTest.gid_mode = GiDPostMode.GiD_PostBinary |
| float PecletTest.mesh_name = 0.0 |
| PecletTest.model_part = ModelPart("DummyPart"); |
| PecletTest.model_part_io = ModelPartIO("PecletTest") |
| PecletTest.multifile = MultiFileFlag.SingleFile |
| float PecletTest.nnodes = 0.0 |
| int PecletTest.step = 0 |
| PecletTest.Temp = node.GetSolutionStepValue(TEMPERATURE) |
| float PecletTest.time = 0.0 |
| float PecletTest.velocity = 1.0 |
| PecletTest.write_conditions = WriteConditionsFlag.WriteElementsOnly |


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|---|
| Name | Created By | Deleted | |
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| {{environment.createdBy}} | {{environment.isDeleted}} | {{environment.isDeleted}} |


--- creation_epoch:<PHONE_NUMBER> lastmod_epoch:<PHONE_NUMBER> categories: Security title: aws-api-key-auto-rotator and InnoTech OKC presentation --- My tool I wrote for rotating on-premise (not in cloud) service credentials used for AWS cloud. I presented this at InnoTech OKC 2017.


WITNESS LIST Human Services Committee May 5, 2003-2:30P HB 1665 For: Hicks, Patsy (Self) SB 60 For: Gant, Melaine (Mental Health Association of Texas) Gothart-Barron, Sherri (Chance Gothart) Hyatt, Deborah (Texas Federation of Families for Children Mental Health) Thyssen, Monica (Advocacy Inc.) SB 669 For: Kenny, Robert (Self) Against: McCown, F. Scott (CPPP) SB 1073 On: Gadberry, Gavin (Texas Health Care Association) SB 1204 For: Fenz, Caton (Harris County Comm. Court) Llyod, Roberta (Mike Stafford, Harris County) Against: Gadberry, Gavin (Texas Health Care Association) SB 1489 On: Benham, Rose (Children Protective Services)


This directory contains non-portable Oberon-7 modules intended for the POSIX environment and compiled with the OBNC compiler.


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Amid protests, Morales says 'coup' risks democracy in Bolivia
Bolivian leader's statement on Twitter comes as police join opposition protests following disputed election result.
Bolivian President Evo Morales denounced what he called a coup by violent groups on Saturday, as police officers joined opposition protests amid a weeks-long standoff over a disputed election.
Morales, Latin America's longest-standing leader, won the election on October 20 but the vote count had been inexplicably halted for nearly a day.
Allegations of fraud have led to protests, strikes and roadblocks.
More:
Morales took to Twitter to denounce the police rebellion as a coup.
"Our democracy is at risk due to the coup d'etat that violent groups have launched that undermine the constitutional order," he wrote, as he called on Bolivians to protect their democracy and constitution.
"Before the international community, we denounce this attack on the rule of law."
Morales earlier held an emergency meeting with ministers.
Luis Fernando Camacho, a civic leader from the eastern city of Santa Cruz who has become a symbol of the opposition, replied to Morales's tweet, saying: "We have not come to overthrow a president, we have come to free Bolivia from its dictatorship."
Camacho plans to lead a march to the government palace on Monday with a symbolic pre-written resignation letter for Morales to sign.
Bolivians rallied again in several cities on Friday.
Reports of police joining the protests added pressure on Morales.
In the city of Cochabamba, the scene of violent clashes, journalists of Reuters news agency reported seeing police officers protesting on the roof of their headquarters in an apparent act of disobedience against the government.
The foreign ministry said in a statement on Saturday the police officers had "abandoned their constitutional role of ensuring the security of society and state institutions".
In the small town of Vinto, the mayor, who hails from the ruling Mas party was attacked by opposition protesters on Thursday. They dragged her through the streets and assaulted her shouting "murderer", according to local reports.
The attack followed reports that two anti-government protesters had been killed, alleged deaths which prompted demonstrators to march towards the city town hall.
After hearing the rumours, a crowd marched to the town hall and lashed out at the mayor.


Sorter for local food to the wf house. Pick your sources, and hit the Start button.
Click on the character you like better from the two, or tie them if you like them equally or don't know them.
Keyboard controls during sorting: H/← (pick left)
J/↓ (undo)
K/↑ (tie)
L/→ (pick right)
S (save progress).
Before sorting: S/Enter (start sorting)
L (load progress).
1/2/3 always correspond to the first/second/third buttons.
Inspired by this site and using Execfera's Touhou sorter.
Character Art from the GuP Wiki.


Hi all,
The last I saw on the blogs were "Update: The single CT Home Energy Monitor emonGLCD example sketch has been updated to also include proportional red LED PWM brightness control corresponding to the amount of energy being consumed."
I cannot seem to find the code that does this? The single CT Home Energy Monitor sketch does not work for me? What about the switches on the side, is there any code available to use them in the Home Energy Monitor sketch?
Thanks!
Re: LEDs to show consumption
In SolarPV.ino the LED intensity varies according to the power.
SolarPV.ino also uses the switches to change the display. You can make the switches do whatever you want them to do. What is there in the Home Energy Monitor example sketch that you could use the switches for?
Re: LEDs to show consumption
Hi Robert,
I'm actually looking for an example, not sure what the switches could be used for in the Home Energy Monitor, I guess displaying more pages?
Regards
Re: LEDs to show consumption
The immediate problem with that plan is there is not much more memory available in the emonGLCD. The solarPV sketch is very close to the limit, so you might like to look at that, both as an idea for extra pages, but also to give you an idea of how much (or how little) can be added.
Re: LEDs to show consumption
Thanks Robert, will do


OK, I'm finally getting around to write about this movie, which I saw this past weekend. From a business point of view, it's a little disappointing that the show wasn't sold out. I suppose that simply reflects how South Park has a certain audience, and this audience has probably gone and seen it on opening weekend, and not the subsequent weekend like me.
The film is truly epic. Most TV shows that go on to become films have a problem expanding out of their 30-minute time slots into something larger, leaving numerous soft spots. Witness the Beavis and Butthead movie, any number of Saturday Night Live derived films, the revivals of certain series from the 1970s. "South Park" succeeds where others have failed: not only does it make the transition from small screen to big, it does it in grand, brilliant fashion, spanning the universe from the deepest pits of Hell to the, uh, celestial spheres of heaven. It's funny throughout: the number of minutes you spend not chuckling or laughing out loud can be counted on your fingers. Granted, this is mostly gross out humor and the amusement of seeing third graders curse floridly, and it's just damn funny. Yes, we've known all along that South Park is a raw-for-TV show with a even more raw R-rated movie inside waiting to break out, but seeing Cartman let loose, a sort of apotheosis of Eric, is a wonder in itself. It's what we've been waiting for.
"South Park" even has a point to make, particularly relevant after the Littleton, CO, shootings, where everything remotely connected to the media or computer gaming industry was blamed for the violence of two disturbed individuals. This is not a simple, potty-mouthed movie, but a sharp bit of social commentary as well. A stand is taken, and I leave it to the movie to make its argument.
One nice thing about this transition from small to big screen is that they don't try to drag out every peripheral character that's ever been on the show. Yes, Damien Son of Satan is in the background, as is Jesus and, I think, Pip, but they have no speaking roles. It's like any other SP episode where they have to show a crowd shot: the whole town's there, but no talking. I winced a few times during, say, one of the Star Trek movies where Ensign Bob who appeared in a few episodes back in season 5 and 6 had to get his two lines in. When a TV series makes it to film, it generally tries to hard to be golly gee about the whole thing. SP doesn't.
Not that there aren't references to South Parks Past and the other epics of the Parker/Stone ouvre. Kenny dies in the hospital after having a baked potato put in his chest, an apparent reference to the main song [1] of "Cannibal: The Musical" [2]. And the whole Brian Boitano thing is baffling only if you haven't seen the animated short that started it all, "The Spirit of Christmas" [3].
For that matter, one of the things little remarked upon about this movie is the fact that it's a musical, complete with sophisticated production numbers and a wonderful part towards the end when the main songs of the movie are interwoven into a four-way medley. Broadway shows are parodied -- Les Mis was skewered -- as well as Disney animated films -- Satan as the Little Mermaid. This shouldn't be surprising giving the large musical content of the weekly show, as well as previous Parker-Stone efforts like "Cannibal" (all singing, all dancing, all flesh-eating).
So, how would Brian Boitano end this review?
[1] http://www.wedgieworld.com/cannibal/shpadoinkle2.html [2] http://us.imdb.com/Reviews/167/16750 [3] http://us.imdb.com/Title?0122264
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
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belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


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{% extends "layout.html" %} {% block title %}{{title}}{% endblock %} {% block content %}
The search string was:
It produced the error:
You might want to check your syntax using jsonlint.com. If your syntax is correct, there may be a bug; please file an issue with a copy-paste of your query.
{% else %} {% if files %}The matched files are listed below. {% if staging_available %} Skip down to the {{staging_dest_displayed}} staging section. {% endif %}
{{macros.file_listing(files)}} {% else %}No files matched this search.
{% endif %} {% if staging_available %}You can launch a task that re-runs this search and copies the matched files to {{staging_dest_displayed}}. Only files that have instances that are directly accessible to the Librarian can be copied.
{% endif %} {% endif %} {% endblock %}


sfEvent defines a system event and its parameters More...
#include <Event.h>
Public Attributes | |
| sfEventType | type |
| Type of the event. More... | |
| sfSizeEvent | size |
| Size event parameters. More... | |
| sfKeyEvent | key |
| Key event parameters. More... | |
| sfTextEvent | text |
| Text event parameters. More... | |
| sfMouseMoveEvent | mouseMove |
| Mouse move event parameters. More... | |
| sfMouseButtonEvent | mouseButton |
| Mouse button event parameters. More... | |
| sfMouseWheelEvent | mouseWheel |
| Mouse wheel event parameters (deprecated) More... | |
| sfMouseWheelScrollEvent | mouseWheelScroll |
| Mouse wheel event parameters. More... | |
| sfJoystickMoveEvent | joystickMove |
| Joystick move event parameters. More... | |
| sfJoystickButtonEvent | joystickButton |
| Joystick button event parameters. More... | |
| sfJoystickConnectEvent | joystickConnect |
| Joystick (dis)connect event parameters. More... | |
| sfTouchEvent | touch |
| Touch events parameters. More... | |
| sfSensorEvent | sensor |
| Sensor event parameters. More... | |
| sfJoystickButtonEvent sfEvent::joystickButton |
| sfJoystickConnectEvent sfEvent::joystickConnect |
| sfJoystickMoveEvent sfEvent::joystickMove |
| sfKeyEvent sfEvent::key |
| sfMouseButtonEvent sfEvent::mouseButton |
| sfMouseMoveEvent sfEvent::mouseMove |
| sfMouseWheelEvent sfEvent::mouseWheel |
| sfMouseWheelScrollEvent sfEvent::mouseWheelScroll |
| sfSensorEvent sfEvent::sensor |
| sfSizeEvent sfEvent::size |
| sfTextEvent sfEvent::text |
| sfTouchEvent sfEvent::touch |


Day
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Month
MARCH
< HANOI >
Monday
16.03
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be prepared
Tuesday
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bring an
Wednesday
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Wear a